A PyTorch implementation of the YOLOX object detection model based on the mmdetection implementation.
Project description
cjm-yolox-pytorch
Install
pip install cjm_yolox_pytorch
How to use
import torch
from cjm_yolox_pytorch.model import MODEL_TYPES, build_model
Select model type
model_type = MODEL_TYPES[0]
model_type
'yolox_tiny'
Build YOLOX model
yolox = build_model(model_type, 19, pretrained=True)
test_inp = torch.randn(1, 3, 256, 256)
with torch.no_grad():
cls_scores, bbox_preds, objectness = yolox(test_inp)
print(f"cls_scores: {[cls_score.shape for cls_score in cls_scores]}")
print(f"bbox_preds: {[bbox_pred.shape for bbox_pred in bbox_preds]}")
print(f"objectness: {[objectness.shape for objectness in objectness]}")
The file ./pretrained_checkpoints/yolox_tiny.pth already exists and overwrite is set to False.
cls_scores: [torch.Size([1, 19, 32, 32]), torch.Size([1, 19, 16, 16]), torch.Size([1, 19, 8, 8])]
bbox_preds: [torch.Size([1, 4, 32, 32]), torch.Size([1, 4, 16, 16]), torch.Size([1, 4, 8, 8])]
objectness: [torch.Size([1, 1, 32, 32]), torch.Size([1, 1, 16, 16]), torch.Size([1, 1, 8, 8])]
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cjm-yolox-pytorch-0.0.143.tar.gz
(23.5 kB
view hashes)
Built Distribution
Close
Hashes for cjm-yolox-pytorch-0.0.143.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 638ba113de0874df60cca038dcbbabc6441c38982758ab4022f18eb16885a905 |
|
MD5 | aeb51a07991813cc65be1f7215d1d59f |
|
BLAKE2b-256 | d17306168c6632d4c056ff7f498c952f43928280e214b8bee2473237aa8e2c94 |
Close
Hashes for cjm_yolox_pytorch-0.0.143-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8f6bbc2c38befe9b3f85ad0514f6dd445a35dc4360c855e262560cf8cd77a2cb |
|
MD5 | 1db8c4507e302e5a2fc08f3b271359f7 |
|
BLAKE2b-256 | e95b11a443621084318c60e2e5afb0ce356219c1a56d86ccf88da2742df3c755 |